1. Field of the Invention
The present invention is directed to sensors. In particular the present invention is directed to piezoelectric sensors.
2. Description of the Related Technology
One type of cancer is melanoma. Melanoma is a malignant tumor of melanocytes, which are melanin-producing cells located predominately in the skin. Melanoma is believed by many clinicians to be one of the most aggressive types of malignancies. Although melanoma accounts for only 4 percent of all skin cancers, it is responsible for 80 percent of skin cancer deaths, and its incidence and mortality have increased steadily over the past three decades. It is estimated that approximately 76,690 new cases of invasive melanoma will be diagnosed in the United States in 2013, and about 9,480 people will die of the disease [1]. The earliest stage of melanoma grows radially within the epidermis, and becomes increasingly lethal as it advances deeper into the skin. Melanoma thickness (illustrated in FIG. 1), or Breslow Thickness (BT), is the most important histopathological factor for staging and is closely related to survival rate [2]. The five-year survival rate is 95% if the tumor thickness is less than 1 mm, while the survival rate is reduced to 50% when the tumor thickness is greater than 4 mm [3, 4].
BT is commonly measured by removing a portion of the lesion by a shave or punch biopsy and then histologically examining the sample. This method, when completed by experienced dermatologists, has been shown to underestimate the BT about 12% to 20% of the time. Complete excision of the lesion is the most accurate method of measuring BT, but this is often impossible due to the lesion covering too large a surface area or being in an aesthetically sensitive location [5]. Moreover, 80% of malpractice claims relating to melanoma cite incomplete biopsy specimens as a contributing factor in disease progression [6].
Another issue with melanoma surgery is that the parameters for excision depth and surgical margins are highly inconsistent among dermatologists in terms of completely eliminating the lesion [7, 8]. For example, if the melanoma thickness is <1 mm (<2 mm) then a lateral area of 1 cm (2 cm) is removed. As a result, a tedious and time-consuming process called Mohs surgery is commonly used to determine if the entirety of a malignant lesion has been removed. During this procedure, a surgeon serially removes and histologically examines sections of the lesion until the margins are clear of malignant cells. Therefore, a tool that can conclusively and non-invasively measure the thickness of skin lesions in vivo would be invaluable for improving the accuracy of the assessment of melanoma staging, and for determining the margins for surgical removal before the operation.
Another type of cancer is breast cancer, which has been the cancer type with one of the highest fatality rates for women over the past several decades. It is the most common non-skin malignancy diagnosed in women. In the United States, there will be 232,340 invasive breast cancer cases and 64,640 carcinomas in situ diagnosed in 2013 [9]. It is estimated that 500,000 women in the world will die from breast cancer each year [10].
Accurate preoperative assessment of breast tumor locations and sizes in three dimensions (3D) are important for both biopsies and surgeries [11]. Clinical breast examination (CBE), ultrasound, mammography, and magnetic resonance imaging (MRI) are the main currently used breast tumor detection and localization methodologies [12, 13]. CBE cannot provide a quantitative value of the tumor size and has difficulty detecting lesions with indistinct borders, lesions in large breasts, and non-palpable lesions [14, 15]. Mammography, MRI, and ultrasound project a 3D tumor on a two dimensional (2D) plane. Although mammography takes two pictures, one viewed from top to bottom and the other from a 45° angle, it is still difficult to pinpoint the actual location and extent of the tumor using this method. Compression of the breast can also lead to distortion of the location and extent of the tumor. Variations in the distance between the lesion and mammogram film and vague lesion boundaries can introduce error to the measurements [14]. Moreover, standard imaging methods do not always capture the maximum tumor extent [16]. In addition, patients are in a different position during typical mammography imaging than the supine position that is typically used during surgery. Such differences can further distort the 3D localization of the tumor.
While ultrasound is widely available and does not require compression of the breast it frequently underestimates the tumor size [17-19]. This may lead to incomplete excision in a lumpectomy [11]. Ultrasound also does not detect all types of tumors.
MRI requires compression of the tumor for accurate detection. A recent study indicated that MRI also frequently underestimates the size of breast lesions especially those of ductal carcinoma in situ (DCIS) [20]. The discordance between the tumor size on MRI and the pathological size may contribute to the number of re-excisions required for patients that undergo lumpectomy procedures.
A technique that can detect not only the presence but also the 3D location of the tumor, and particularly the depth location of the tumor, will provide more accurate biopsies and surgeries. Precise measurement of tumor sizes in 3D is also important to monitor the response to chemotherapy for breast tumors. It is well known that breast tumors are stiffer than the surrounding normal tissue. This property allows breast tumors to be detected by contrasting tissue stiffness, and can allow 3D mechanical imaging and sizing of breast tumors.
SureTouch™, a breast tumor imaging system, developed by Egorov et al., reconstructs the 3D tumor image from a series of 2D pressure distribution maps based on the assumption that a higher compression force leads to a better representation of the deeper structures in a 2D pressure map [21-23]. However, the accuracy of the SureTouch™ in determining the depth profile of breast cancer tumors has not been reported [23]. The smallest size of inclusions detected by this method in a breast model was 5 mm [22].
Another approach employs a tactile sensation imaging system (TSIS). This approach first generates tactile sensation imaging data and correlates this data using finite element simulations, followed by applying an artificial neural network to extract the size, depth, and Young's modulus of the tumor [24-26]. The smallest size of inclusions detected by this method in the models was 2 mm. This method was based on the assumption that all the tumors were spherical in shape. This was not an accurate assumption since most of the breast tumors had irregular or asymmetric shapes [27, 28].
A piezoelectric finger (PEF) is a type of sensor that can measure tissue elastic modulus (E) in vivo by contacting the PEF with the tissue [29-32]. A tumor could be directly detected by contrasting the stiffness of the tumor, as indicated by the measured tissue elastic modulus, with the stiffness of surrounding normal tissue. What makes PEF different from the tactile imaging technologies is that PEF measures the elastic modulus of the tissue but not the pressure distribution. This distinction makes PEF measurements insensitive to the pressure applied to the device [33] during the data collection process, which in turn makes the measurement less dependent on the operator of the device. Also, this method does not require an algorithm to remove the background pressure profile [22, 23] as do some other tactile imaging methods.
The fabrication and characterization of PEFs can be found in references [29-31]. PEFs have been used to detect breast cancer by contrasting the stiffness of the lesion with that of the surrounding tissue without the need to employ inversion simulations or pattern recognition software (see WO 2009/140660, the disclosure of which is hereby incorporated herein by reference in its entirety). PEFs are also described in U.S. Pat. No. 7,497,133, the disclosure of which is also hereby incorporated herein by reference.
In previous in vivo studies, PEFs have been tested on 40 patients and these tests have demonstrated that PEFs are capable of detecting most types of breast tumors in vivo, including at least fibroadenomas, cysts, invasive carcinomas and ductal carcinomas in situ. The overall sensitivity of the PEF test was 87%. In women 40 years and younger, the overall sensitivity was 100%. The smallest tumor detected by a PEF was 2×5 mm [33]. Model tissue studies have also shown that the detectable depth obtained by using a PEF was twice that of the probe size of the PEF [31]. In other words, with a larger probe size a PEF can assess the elastic response of tissue at greater depths from the tissue surface.